SBC logo Authors: Amine Heddad, Andrea Krings, Markus Brameier and Bob MacCallum, Stockholm Bioinformatics Center, Stockholm University, Sweden.

NucPred

Fetching P30415 from www.uniprot.org...

The NucPred score for your sequence is 0.98 (see score help below)

   1  MGAQDRPQCHFDIEINREPVGRIMFQLFSDICPKTCKNFLCLCSGEKGLG    50
  51  KTTGKKLCYKGSTFHRVVKNFMIQGGDFSEGNGKGGESIYGGYFKDENFI   100
 101  LKHDRAFLLSMANRGKHTNGSQFFITTKPAPHLDGVHVVFGLVISGFEVI   150
 151  EQIENLKTDAASRPYADVRVIDCGVLATKLTKDVFEKKRKKPTCSEGSDS   200
 201  SSRSSSSSESSSESEVERETIRRRRHKRRPKVRHAKKRRKEMSSSEEPRR   250
 251  KRTVSPEGYSERSDVNEKRSVDSNTKREKPVVRPEEIPPVPENRFLLRRD   300
 301  MPAITVEPEQNIPDVAPVVSDQKPSVSKSGRKIKGRGTIRYHTPPRSRSH   350
 351  SESKDDDSSETPPHWKEEMQRLRAYRPPSGEKWSKGDKLSDPCSSRWDER   400
 401  SLSQRSRSWSYNGYYSDLSTARHSDGHHKKHRKEKKFKHKKKAKKQKHCR   450
 451  RHRQTKKRRIVMPDLEPSRSPTHRMKSSCVRERRSRASSSSSHHSSKRDW   500
 501  SKSDQDDGSASTHSSRDSYRSKSHSRSDSRGSSRSRAVSKSSSRSLNRSK   550
 551  SRSSSRSGPRRTSISPKKPAQLSENKPVKTEPLRPSVPQNGNVLVQPVAA   600
 601  ENIPVIPLSDSPPPSRWKPGQKPWKPSYERIQEMKAKTTHLLPVQSTYSL   650
 651  TNIKATVSSSSYHKREKPSESDGSAYSKYSDRSSGSSGRSGSKSSRSRSS   700
 701  SRSYTRSRSRSLPTSRSLSRSPSSRSHSPNKYSDGSQHSRSSSYTSVSSD   750
 751  DGRRAMFRSNRKKSVTSHKRHRSNSEKTLHSKYVRGREKSSRHRKYSESR   800
 801  SSLDYSSDSDQSHVQVYSAPEKEKQGKVEALNDKQGKGREEGKPKPEWEC   850
 851  PRSKKRTPKDHSRDDSVSKGKNCAGSKWDSESNSEQDVTKSRKSDPRRGS   900
 901  EKEEGEASSDSESEVGQSHIKAKPPAKPPTSTFLPGSDGAWKSRRPQSSA   950
 951  SESESSCSNLGNIRGEPQKQKHSKDDLKGDHTKRAREKSKAKKDKKHKAP  1000
1001  KRKQAFHWQPPLEFGDDEEEEMNGKQVTQDPKEKRHVSEKCEAVKDGIPN  1050
1051  VEKTCDEGSSPSKPKKGTLEQDPLAEGGHDPSSCPAPLKVEDNTASSPPS  1100
1101  AQHLEEHGPGGGEDVLQTDDNMEICTPDRTSPAKGEVVSPLANHRLDSPE  1150
1151  VNIIPEQDECMAHPRAGGEQESSMSESKTLGESGVKQDSSTSVTSPVETS  1200
1201  GKKEGAEKSQMNLTDKWKPLQGVGNLSVSTATTSSALDVKALSTVPEVKP  1250
1251  QGLRIEIKSKNKVRPGSLFDEVRKTARLNRRPRNQESSSDDQTPSRDGDS  1300
1301  QSRSPHRSRSKSETKSRHRTRSVSYSHSRSRSRSSTSSYRSRSYSRSRSR  1350
1351  DWYSRGRTRSRSSSYGSFHSHRTSSRSRSRSSSYDLHSRSRSYTYDSYYS  1400
1401  RSRSRSRSQRSDSYHRGRSYNRRSRSGRSYGSDSESDRSYSHHRSPSESS  1450
1451  RYS                                                 1453

Positively and negatively influencing subsequences are coloured according to the following scale:

(non-nuclear) negative ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| positive (nuclear)

with NucPred



If you find NucPred useful, please cite this paper:
NucPred - Predicting Nuclear Localization of Proteins. Brameier M, Krings A, Maccallum RM. Bioinformatics, 2007. PubMed id: 17332022
The authors also look forward to your comments and suggestions.

What does the NucPred score mean?

You have to decide on a NucPred score threshold. Sequences which score greater than or equal to this threshold are predicted to spend some time in the nucleus. Higher thresholds yield fewer predicted nuclear proteins, but these predictions are more accurate (you can have higher confidence in them). The table below gives more details of the performance of NucPred estimated using the sequences it was trained on (by cross-validation). Another benchmark is available in the Bioinformatics 2007 paper.

NucPred score threshold Specificity Sensitivity
see above fraction of proteins predicted to be nuclear that actually are nuclear fraction of true nuclear proteins that are predicted (coverage)
0.10 0.45 0.88
0.20 0.52 0.83
0.30 0.57 0.77
0.40 0.63 0.69
0.50 0.70 0.62
0.60 0.71 0.53
0.70 0.81 0.44
0.80 0.84 0.32
0.90 0.88 0.21
1.00 1.00 0.02

Sequences which score >= 0.8 with NucPred and which are predicted by PredictNLS to contain an NLS have been shown to be 93% correct with a coverage of 16%. (PredictNLS by itself is 87% correct with 26% coverage on the same data.)

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